A multi-point remote collaborative interaction method and system based on power communication network operation and maintenance

Abstract

The application relates to a multi-point remote collaborative interaction method and system based on power communication network operation and maintenance, and belongs to the technical field of power communication, and aims to solve the problems of low node state sensing accuracy, unbalanced bandwidth allocation, poor network state adaptability and interrupted collaborative tasks in the prior art. The method comprises the following steps: collecting the periodic round-trip delay of the power node and the center node to form a delay table, calculating a bandwidth allocation coefficient based on the delay table and determining an available bandwidth share; dynamically adjusting the uplink and downlink bandwidth ratio; dividing the data flow priority and performing collaborative simulation, and recording the transmission exception queue; performing task redistribution and bandwidth optimization based on the exception queue. Through the above method, the bandwidth resource and the node state are accurately matched, the network state is dynamically adapted, and the collaborative task is stably executed, so that the bandwidth resource utilization and the remote collaborative interaction reliability are effectively improved.

Description

Technical Field

[0001] This invention belongs to the field of power communication technology, specifically relating to a multi-point remote collaborative interaction method and system based on power communication network operation and maintenance. Background Technology

[0002] In the existing operation and maintenance management of power communication networks, multi-point remote collaborative tasks mainly rely on manual scheduling or static control strategies based on the state of a single node. While these strategies can achieve basic collaboration under small-scale network or low-load conditions, their scheduling efficiency and reliability significantly decrease when facing large-scale power networks, heterogeneous node distribution, and real-time load fluctuations. With the rapid development of smart grids and distributed energy systems, the types of nodes and data traffic in power communication networks exhibit multi-source, multi-speed, and dynamically changing characteristics. Traditional single-node or single-dimensional scheduling methods are insufficient to meet real-time collaborative requirements. Existing technologies lack the ability to comprehensively analyze and dynamically schedule node latency, bandwidth usage, and data flow priorities, and cannot efficiently address issues such as node packet loss, link congestion, or resource conflicts. This leads to increased latency, discontinuous execution, or failures in remote collaborative tasks, ultimately affecting the stability and reliability of power grid automated operation and maintenance.

[0003] In view of this, it is very necessary to provide a multi-point remote collaborative interaction method and system based on power communication network operation and maintenance to solve the above-mentioned defects in the prior art. Summary of the Invention

[0004] To address the technical problems of low accuracy in node status perception, poor adaptability of bandwidth allocation to actual load, and weak stability in remote collaborative task execution in existing technologies, this invention provides a multi-point remote collaborative interaction method and system based on power communication network operation and maintenance to solve the above-mentioned technical problems.

[0005] In a first aspect, the present invention provides a multi-point remote collaborative interaction method based on power communication network operation and maintenance, comprising: Step S1: Collect the periodic round-trip delay between each power node and the central node to form a delay table. Calculate the bandwidth allocation coefficient based on the delay table and determine the available bandwidth share for each power node using the bandwidth allocation coefficient. The periodic round-trip delay between each power node and the central node is collected to form a delay table, which includes: sending a timestamped probe signal to each power node through the central node, the power node receiving the probe signal and returning a response message, the central node receiving the response message and recording the sending time and response time of the probe signal, and calculating the single round-trip delay. Arrange multiple consecutive round-trip delays in chronological order to form a delay sampling sequence, divide the time window into fixed lengths, and calculate the average value of all round-trip delays within each time window; Adjust the sliding step size according to the average difference of the single round-trip delay of two adjacent time windows, move the time window according to the adjusted sliding step size, and mark the sampling points where the difference between the single round-trip delay and the average single round-trip delay of the current time window exceeds the preset range as noise residual points. For all noise residue points, spline interpolation is used to correct the data. The corrected time delay sampling sequence is re-divided into time windows and the average value is calculated. The time window shifting and noise correction steps are repeated to generate a smooth time delay characteristic curve. The delay value of each power node is extracted based on the delay characteristic curve. The delay interval is divided according to the range of delay value. The average round-trip delay of each power node is obtained by using the corresponding average value calculation method for different delay intervals. The identification information and average round-trip delay of all power nodes are summarized to form a delay table. The delay range is divided into low delay range, normal delay range, and high delay range according to the delay value range; Among them, The range is divided into a low latency range, and the range of latency values ​​between a preset low latency threshold and a preset high latency threshold is divided into a normal latency range. The range is divided into high-latency intervals; For the low-latency range, the arithmetic mean is used to calculate the average round-trip time, and the mathematical expression is: ,in, The average round-trip time for the low-latency interval, Let k be the round-trip delay within the low-latency interval. This represents the total number of round-trip delays within the low-latency interval. For the normal delay range, the average round-trip time is calculated using a weighted average, and the mathematical expression is: ,in, The average round-trip time within the normal delay range. This represents the k-th round-trip delay within the normal delay interval. This is the time weighting coefficient for the k-th single round-trip delay. This represents the total number of round-trip delays within the normal delay interval. For the high-latency interval, the average round-trip time is calculated using a sliding window averaging method. The single round-trip time within the high-latency interval is iterated through using a fixed window length and step size. The average value of each sliding window is calculated and taken as the average round-trip time for the high-latency interval. The average round-trip time of the low-delay interval, the average round-trip time of the normal-delay interval, and the average round-trip time of the high-delay interval are used as the average round-trip time of the corresponding power nodes.

[0006] The bandwidth allocation coefficient is calculated based on the delay table, including: Create a scheduling list, extract the average round-trip time of each power node in the delay table, and mark the delay status of each power node in the scheduling list according to the delay interval to which the average round-trip time belongs. If the average round-trip time belongs to the low delay interval, it is marked as low delay status; if it belongs to the normal delay interval, it is marked as normal delay status; and if it belongs to the high delay interval, it is marked as high delay status. The system presets bandwidth weights for different latency states and allocation weights for different data stream priorities. For power nodes in low latency states, the bandwidth of the node is preferentially allocated to the high-priority data streams of the node according to the allocation weights. For power nodes in normal latency states, the bandwidth allocation between the high-priority and medium-priority data streams of the node is balanced according to the allocation weights. For power nodes in high latency states, the system guarantees the transmission of the low-priority data streams of the node according to the allocation weights. Set a fixed bandwidth allocation rate, group bandwidth allocation instructions by power node, and push the bandwidth allocation instructions to each power node in batches; The link utilization rate, packet loss rate and buffer queue length of each power node are collected in real time as network occupancy indicators. The bandwidth allocation coefficient of the corresponding power node is dynamically adjusted according to the deviation between the network occupancy indicators and the preset indicator thresholds. The available bandwidth share for each power node is determined by the bandwidth allocation factor, which includes: The bandwidth occupancy change rate of each power node is calculated using the bandwidth allocation coefficient. The bandwidth usage trend of each power node is determined by the bandwidth occupancy change rate. The positive and negative signs of the bandwidth usage trend of each power node are analyzed to identify the current bandwidth status of the power node and obtain the dynamic trend of node bandwidth. The bandwidth status includes bandwidth strain and bandwidth idle status. A positive sign corresponds to bandwidth strain and a negative sign corresponds to bandwidth idle status. Cross-validation of link capacity allocation strategies is performed based on the dynamic trend of power node bandwidth. If the validation result is consistent with the dynamic trend of power node bandwidth, the network scheduling code is recorded. Obtain the allocation instruction for each power node's smallest unit in the network scheduling code, and map the allocation instruction to the target bandwidth value of the power node's smallest unit; For each power node's smallest unit, the target bandwidth value is weighted and fused with the power node's historical bandwidth occupancy value to generate a preliminary bandwidth allocation vector; A physical link table for power nodes is established based on the initial bandwidth allocation vector. The physical link table is used to identify shared nodes. The vector intervals of the shared nodes are cross-compared one by one to determine the overlapping time period of bandwidth allocation. During the overlapping period of bandwidth allocation, conflicting nodes are marked, and conflicting node information is read based on the conflicting nodes. The total bandwidth between power nodes is compared to determine the allocation conflict anomaly. The total bandwidth of the smallest connected power nodes is summed and compared with the maximum carrying bandwidth threshold to identify the smallest power node that exceeds the link capacity limit. Conflict correction is performed based on the smallest unit of power nodes that exceed the link capacity limit, and a bandwidth allocation vector is constructed. The available bandwidth of each power node is predicted by extrapolating the bandwidth allocation vector, and the available bandwidth share of each power node is determined based on the predicted available bandwidth.

[0007] The above technical solution acquires single round-trip delay by sending timestamped probe signals from the central node. A smooth delay characteristic curve is generated through time window division, dynamic sliding step size adjustment, and spline interpolation correction. This curve is then combined with differentiated average values ​​for low-latency, normal-latency, and high-latency intervals to improve the accuracy and adaptability of the average round-trip delay. Node delay status is marked using a scheduling list, and bandwidth allocation is weighted by both delay status and data flow priority. This, coupled with batch distribution and real-time dynamic adjustment of network indicators, achieves precise and dynamic optimization of bandwidth allocation. Based on bandwidth allocation coefficient analysis of node bandwidth dynamics, a bandwidth allocation vector is constructed using network scheduling codes. Combined with shared node identification, bandwidth overlap judgment, and conflict correction mechanisms, the available bandwidth share for each power node is accurately determined, avoiding allocation conflicts and link overload, and comprehensively improving bandwidth utilization and allocation rationality.

[0008] Step S2: Allocate available bandwidth to power nodes, detect the network status of each power node, and dynamically adjust the bandwidth ratio in the uplink and downlink directions according to the network status; The dynamic adjustment of the uplink and downlink bandwidth ratio based on network status includes: calculating the ratio of the uplink bandwidth occupancy per unit time to the total uplink bandwidth as the instantaneous occupancy rate, and determining the uplink bandwidth competition intensity of each power node by the magnitude of the instantaneous occupancy rate. Each power node is assigned a ranking number based on the intensity of uplink bandwidth competition, from highest to lowest. Uplink bandwidth shares are then allocated according to the order of the ranking numbers, with power nodes ranked earlier receiving a larger share of uplink bandwidth. The number of instructions transmitted per unit time by downlink nodes is used as the instruction transmission density. Nodes whose instruction transmission density exceeds a preset density threshold are marked as downlink congestion points. The time difference between sending and receiving instructions at congestion points is continuously monitored as the instruction latency. The increase in bandwidth is calculated based on the difference between the instruction latency and the preset latency threshold, and the downlink bandwidth share is allocated to each downlink node according to the increase in bandwidth. If the uplink bandwidth allocation value exceeds the maximum carrying capacity of the corresponding power node link, the uplink bandwidth allocation value of the power node is limited to a fixed percentage of the maximum carrying capacity, the power node is marked as a bandwidth-limited node, and the remaining unallocated uplink bandwidth is reallocated to the power node with the next highest sequence number. The formula for calculating the allocation of uplink bandwidth share based on the order of the sequence number is as follows:

[0009] in, Let be the uplink bandwidth share of the i-th power node. Let N be the instantaneous uplink occupancy rate of the i-th power node, and N be the total number of power nodes participating in uplink bandwidth allocation. This represents the total available uplink bandwidth. The formula for allocating downlink bandwidth shares to each downlink node according to the increase in bandwidth is as follows:

[0010] in, Let i be the downlink bandwidth share of the i-th power node. For the basic bandwidth of power nodes, For instruction latency, This is the bandwidth adjustment factor.

[0011] The uplink bandwidth allocation and downlink bandwidth share are integrated into a single comprehensive bandwidth share, which is expressed mathematically as follows:

[0012] That , These are the weighting coefficients.

[0013] The above scheme allocates uplink and downlink bandwidth differently based on uplink competition intensity and downlink congestion delay. Combined with link carrying capacity limitations and remaining bandwidth reallocation, it optimizes the adaptability of uplink and downlink bandwidth ratios, reduces link congestion risk, and improves data transmission efficiency. The logic of uplink bandwidth share allocation is clarified through quantitative formulas, making the allocation results more scientific and operable, and ensuring fair and reasonable allocation of uplink bandwidth resources among power nodes.

[0014] Step S3: Prioritize data streams according to bandwidth ratio, perform multi-point remote collaborative simulation based on data stream priority, and record the transmission anomaly queue if the packet loss rate of the power node is higher than the preset packet loss threshold. Multi-point remote collaborative simulation based on data stream priority includes: dividing the data to be transmitted by each power node into multiple priority queues according to the data stream priority from high to low. Each priority queue contains only the same priority data stream of a single power node, and all priority queues form a candidate scheduling queue set. Multi-point remote collaborative simulation is started according to the preset simulation duration. Data streams in the candidate scheduling queue are transmitted in order of priority. The total number of data packets sent and received, link occupancy rate and round-trip delay of each power node are recorded in real time. The packet loss rate of each power node is calculated based on the total number of data packets sent and the total number of data packets successfully received. Power nodes with packet loss rates higher than the preset packet loss threshold and their corresponding priority queue information are included in the transmission anomaly queue.

[0015] By adopting the above technical solution, data streams are divided according to priority and a candidate scheduling queue set is constructed. High packet loss rate nodes are identified in advance and abnormal queues are recorded through collaborative simulation, providing accurate basis for task reassignment and reducing the risk of collaborative task execution interruption.

[0016] Step S4: Perform task reallocation based on the transmission anomaly queue, determine the bandwidth optimization allocation share, and use the bandwidth optimization allocation share to correct the transmission anomaly queue in order to execute multi-point remote collaborative interaction tasks; Task reallocation based on the transmission anomaly queue includes: extracting the identification information of each abnormal power node in the transmission anomaly queue, locating the physical link where the abnormal power node is located, and collecting the ratio of the bandwidth occupancy of each physical link per unit time to the maximum carrying bandwidth of the link as the link occupancy rate. Physical links with a link occupancy rate higher than a first preset threshold are marked as high-load links, and physical links with a link occupancy rate lower than a second preset threshold are marked as low-load links. Identify all data streams carried on high-load links, filter out low-priority data streams as non-critical tasks, and migrate non-critical tasks to low-load links. During the migration process, the link occupancy rate of high-load links and low-load links is collected once per second. The bandwidth allocation is dynamically adjusted based on the changes in link occupancy rate to keep the high-load link occupancy rate within a preset reasonable range and the low-load link occupancy rate does not exceed the preset upper limit.

[0017] By adopting the above technical solution, high and low load links are marked based on link occupancy rate, non-critical tasks on high load links are migrated to low load links, and bandwidth is dynamically adjusted in real time to achieve link load balancing and ensure the continuous and stable execution of collaborative tasks.

[0018] Secondly, the technical solution of the present invention also provides a multi-point remote collaborative interaction system based on the operation and maintenance of power communication networks, including a latency acquisition module, a bandwidth allocation module, a collaborative simulation module, and a task reassignment module; The latency acquisition module collects the periodic round-trip latency between each power node and the central node, forms a latency table, calculates the bandwidth allocation coefficient based on the latency table, and determines the available bandwidth share of each power node through the bandwidth allocation coefficient. The bandwidth allocation module allocates available bandwidth to power nodes, detects the network status of each power node, and dynamically adjusts the bandwidth ratio in the uplink and downlink directions based on the network status. The bandwidth allocation module also includes: The status marking unit is used to create a scheduling list, extract the average round-trip time of each power node in the delay table, and mark the delay status of each power node in the scheduling list according to the delay interval to which the average round-trip time belongs. The weight allocation unit is used to preset the bandwidth weights corresponding to different delay states and the allocation weights corresponding to different data flow priorities, and to allocate the bandwidth of the corresponding data flow to the power nodes with different delay states according to the allocation weights. The coefficient adjustment unit is used to set the bandwidth allocation issuance rate, push bandwidth allocation instructions in batches, collect network occupancy indicators in real time, and dynamically adjust the bandwidth allocation coefficient based on the network occupancy indicators. The share determination unit is used to calculate the bandwidth occupancy change rate using the bandwidth allocation coefficient, determine the dynamic trend of node bandwidth, record the network scheduling code and construct the bandwidth allocation vector, deduce the available bandwidth prediction value based on the bandwidth allocation vector, and determine the available bandwidth share of each power node.

[0019] The collaborative simulation module prioritizes data streams based on bandwidth ratios and performs multi-point remote collaborative simulations based on data stream priorities. If the packet loss rate of a power node exceeds a preset packet loss threshold, a transmission anomaly queue is recorded. The task reassignment module performs task reassignment based on the transmission anomaly queue, determines the bandwidth optimization allocation share, and uses the bandwidth optimization allocation share to correct the transmission anomaly queue in order to execute multi-point remote collaborative interaction tasks.

[0020] The beneficial effects of this invention are as follows: This invention provides a multi-point remote collaborative interaction method and system based on power communication network operation and maintenance. It periodically collects the round-trip delay between power nodes and the central node to form a precise delay table, and calculates bandwidth allocation coefficients based on delay characteristics to determine the available bandwidth share, achieving precise matching between bandwidth resources and node delay status. It optimizes resource allocation logic to adapt to network status changes by dynamically adjusting the uplink and downlink bandwidth ratios and prioritizing data streams. It simulates and predicts packet loss anomalies through multi-point remote collaboration and records transmission anomaly queues. Based on these queues, it performs task reallocation and bandwidth optimization to ensure stable execution of collaborative tasks. The overall solution constructs a complete closed loop of "latency awareness - bandwidth adaptation - anomaly prediction - task optimization," effectively improving bandwidth resource utilization and the reliability of remote collaborative interaction. It solves the problems of bandwidth allocation imbalance, poor network status adaptability, and easy interruption of collaborative tasks in traditional solutions, meeting the core requirements of efficient, stable, and real-time collaboration for large-scale power communication network operation and maintenance.

[0021] Furthermore, the design principle of this invention is reliable, the structure is simple, and it has a very wide range of application prospects. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a flowchart of a multi-point remote collaborative interaction method for operation and maintenance of power communication networks provided by the present invention.

[0024] Figure 2 This is a schematic diagram of a multi-point remote collaborative interaction system based on power communication network operation and maintenance provided by the present invention. Detailed Implementation

[0025] To enable those skilled in the art to better understand the technical solutions of this invention, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this invention.

[0026] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.

[0027] Example 1: like Figure 1 As shown in the figure, this embodiment of the invention provides a multi-point remote collaborative interaction method based on power communication network operation and maintenance, including the following steps: Step S1: Collect the periodic round-trip delay between each power node and the central node to form a delay table. Calculate the bandwidth allocation coefficient based on the delay table and determine the available bandwidth share for each power node using the bandwidth allocation coefficient. In one embodiment, the central node sends a timestamped probe signal to all power nodes at a fixed period (e.g., every 1 second). Each power node immediately returns a response message upon receiving the probe signal. The central node records the transmission and response times and calculates the round-trip time (RTT). The continuously collected RTT data is divided into a 10-second sliding time window with a 5-second step. The average value of each time window is calculated to form a smoothed RTT sequence. Outlier detection is performed on the RTT sequence. If a single RTT deviates from the sliding window average by more than three standard deviations, the data point is marked as a noise residual point. Spline interpolation is used to smooth the noise residual point, resulting in a time delay characteristic curve. The latency characteristic curve is analyzed, and the latency value of the power node is calculated based on the curve. If the latency value is ≤50ms, it is classified as a low latency interval; if the latency value is between 50ms and 150ms, it is classified as a normal latency interval; and if the latency value is ≥150ms, it is classified as a high latency interval. A bandwidth allocation coefficient is calculated based on a preset bandwidth weight for each interval (0.5 for low latency interval, 0.3 for normal latency interval, and 0.2 for high latency interval). The available bandwidth share for each node is obtained by multiplying the total available bandwidth by the bandwidth allocation coefficient.

[0028] In another embodiment, assume there are 12 power nodes in the system. Power nodes 1–4 have an average RTT of 40ms, power nodes 5–8 have an average RTT of 100ms, and power nodes 9–12 have an average RTT of 180ms. The total available bandwidth is 100Mbps. Based on weighted allocation, each power node 1–4 has an available bandwidth of 20Mbps, each power node 5–8 has an available bandwidth of 10Mbps, and each power node 9–12 has an available bandwidth of 5Mbps, forming a power node available bandwidth share table for subsequent scheduling.

[0029] The periodic round-trip delay between each power node and the central node is collected to form a delay table, which includes: sending a timestamped probe signal to each power node through the central node, the power node receiving the probe signal and returning a response message, the central node receiving the response message and recording the sending time and response time of the probe signal, and calculating the single round-trip delay. Arrange multiple consecutive round-trip delays in chronological order to form a delay sampling sequence, divide the time window into fixed lengths, and calculate the average value of all round-trip delays within each time window; In one embodiment, it is assumed that the system has 10 power nodes, and the central node sends probe messages every second. The round-trip time (RTT) for power nodes 1–3 is 42–48 ms, for power nodes 4–6 it is 75–90 ms, and for power nodes 7–10 it is 160–200 ms. A moving average is applied to 10 consecutive sampling points, resulting in an average RTT of 45 ms for power nodes 1–3, 82 ms for power nodes 4–6, and 175 ms for power nodes 7–10. This RTT table provides the data basis for subsequent bandwidth allocation.

[0030] Adjust the sliding step size according to the average difference of the single round-trip delay of two adjacent time windows, move the time window according to the adjusted sliding step size, and mark the sampling points where the difference between the single round-trip delay and the average single round-trip delay of the current time window exceeds the preset range as noise residual points. In one embodiment, the central node receives the time-delay sampling sequence from each power node and divides the time-delay sampling sequence into several consecutive time windows of a fixed length, for example, every 100 milliseconds. An average value is calculated for the sampling points within each time window to represent the time delay level of that time window. The sliding step size is dynamically adjusted based on the change in the average value of consecutive time windows: if the average value of the time window changes significantly, the step size is reduced to enhance the ability to capture short-term fluctuations; if the average value of the time window changes only slightly, the original step size is maintained. Subsequently, within each time window, sampling points that deviate significantly from the average value of the time window are marked as noise residual points for subsequent processing.

[0031] In another embodiment, assuming a power node collects 1000 delay samples within 10 seconds, the time window length is set to 10 sampling points, and the initial step size is 5 points. After calculating the average delay for each time window, if the average value of some time windows changes beyond a preset threshold, the sliding step size of the corresponding time window is reduced to 2 points. After detection, the noise residue points include the 15th, 23rd, 47th, 112th, 305th, and 412th points in the sampling sequence, which are identified as abnormal data points requiring correction.

[0032] For all noise residue points, spline interpolation is used to correct the data. The corrected time delay sampling sequence is re-divided into time windows and the average value of the windows is calculated. The time window shifting and noise correction steps are repeated to generate a smooth time delay characteristic curve. In one embodiment, spline interpolation is used to smooth out identified noise remnants. During interpolation, non-abnormal sampling points around the noise point are used as references to generate smooth replacement values ​​and update the noise point data. After one interpolation, the average value of the time window is recalculated, and the presence of new noise points is re-detected. If noise remnants still exist, interpolation continues. This iteration is repeated until the overall time delay sampling sequence is stable, resulting in a final smooth time delay characteristic curve, which is used for subsequent average time delay calculation or bandwidth allocation.

[0033] In another embodiment, assume the initially identified noise residue points are sampling points 15, 23, 47, 112, 305, and 412, with original delays of 72ms, 65ms, 80ms, 90ms, 120ms, and 110ms, respectively. After interpolation correction using surrounding normal points, the delays of the noise residue points are adjusted to 50ms, 48ms, 52ms, 55ms, 60ms, and 58ms. After replacing the original noise residues, a second check reveals that only sampling point 305 remains abnormal; it is corrected to 60ms using a second interpolation. Ultimately, the entire delay sequence is smooth and continuous, with fluctuations within 5 milliseconds, and can be directly used for node delay analysis.

[0034] The delay value of each power node is extracted based on the delay characteristic curve. The delay interval is divided according to the range of delay value. The average round-trip delay of each power node is obtained by using the corresponding average value calculation method for different delay intervals. The identification information and average round-trip delay of all power nodes are summarized to form a delay table. In one embodiment, the central node groups the collected round-trip times by node, generating a delay sampling sequence for each node. Each delay sequence uses a 10-second sliding window with a 5-second step. The average and standard deviation within the sliding window are calculated, and cubic spline interpolation is used to smooth the connection of the average values ​​from each sliding window, resulting in a continuous delay characteristic curve. Based on the delay characteristic curve, the average round-trip time of each power node is calculated and sorted from low to high, assigning a unique number to each power node. Simultaneously, the power node ID, average round-trip time, and fluctuation range are summarized to form a delay table. The delay table can be used to determine link health status and dynamically adjust bandwidth strategies.

[0035] In another embodiment, delay sampling sequences of power nodes 1-10 are collected. The delay sampling sequences of power nodes 1-3 are [44,46,45,43,47], [80,82,85,79,83], and [178,175,180,182,177], respectively. After averaging via a sliding window, the average round-trip times for power nodes 1-3 are 45ms, 82ms, and 178ms, respectively, and so on. The power nodes are then sorted from lowest to highest average round-trip time, numbered Node 1 → Node 2 → Node 3 → ... → Node 10, forming a complete delay table to provide basic data for bandwidth allocation and remote collaborative scheduling.

[0036] The delay range is divided into low delay range, normal delay range, and high delay range according to the range of delay values; Among them, The range is divided into a low latency range, and the range of latency values ​​between a preset low latency threshold and a preset high latency threshold is divided into a normal latency range. The range is divided into high-latency intervals; In one embodiment, the central node calculates the current round-trip time (RTT) point-by-point based on the obtained RTT characteristic curves of each power node. If the RTT is ≤50ms, it is classified as a low-latency interval; if 50ms < RTT < 150ms, it is classified as a normal-latency interval; and if the RTT is ≥150ms, it is classified as a high-latency interval. The RTT status of each power node is dynamically updated over time. To prevent misclassification due to short-term fluctuations, median filtering can be applied to the RTT values ​​of each power node over a consecutive 5-second period to ensure smooth and continuous RTT partitioning. The RTT partitioning results can serve as the basis for subsequent bandwidth allocation strategies and data flow priority calculations.

[0037] In another embodiment, assuming the system has 10 power nodes, the round-trip times (RTTs) for power nodes 1-3 are [42, 48, 45, 47, 44, 46, 49, 43, 45, 46] ms during a 10-second sampling period, the RTTs for power nodes 4-6 are [55, 60, 58, 62, 57, 65, 61, 59, 63, 60] ms, and the RTTs for power nodes 7-10 are [155, 162, 158, 170, 165, 160, 168, 172, 159, 166] ms. Based on thresholds, power nodes 1-3 fall into the low-latency range, power nodes 4-6 fall into the normal-latency range, and power nodes 7-10 fall into the high-latency range. This classification intuitively reflects the link performance of each node and facilitates subsequent calculation of the average RTT.

[0038] For the low-latency range, the arithmetic mean is used to calculate the average round-trip time, and the mathematical expression is: ,in, For the average round-trip time in the low-latency zone, Let k be the single round-trip delay within the low-latency interval. This represents the total number of round-trip delays within the low-latency interval. For the normal delay range, the average round-trip time is calculated using a weighted average, and the mathematical expression is: ,in, The average round-trip time within the normal delay range. This represents the k-th round-trip delay within the normal delay interval. This is the time weighting coefficient for the k-th single round-trip delay. This represents the total number of round-trip delays within the normal delay interval. For the high-latency interval, the average round-trip time is calculated using a sliding window averaging method. The single round-trip time within the high-latency interval is iterated through using a fixed window length and step size. The average value of each sliding window is calculated and taken as the average round-trip time for the high-latency interval. The average round-trip time of the low-delay interval, the average round-trip time of the normal-delay interval, and the average round-trip time of the high-delay interval are used as the average round-trip time of the corresponding power nodes.

[0039] In one embodiment, for the low-latency interval, the average round-trip time is calculated directly using the arithmetic mean; for the normal-latency interval, a time weighting coefficient is introduced. (The time weighting coefficient is set according to the network load or historical stability at the sampling time.) The average round-trip time of power nodes is calculated using a weighted average. For high-latency intervals, a sliding window average (e.g., a 10-second window with a 5-second step) is used to calculate a local average to suppress the impact of sudden latency spikes on the average. Finally, the arithmetic mean of the low-latency interval, the weighted average of the normal-latency interval, and the sliding average of the high-latency interval are integrated to obtain the comprehensive average round-trip time of each power node, which is used for bandwidth allocation, task scheduling, and priority determination of multi-point remote collaborative interaction.

[0040] In another embodiment, assuming the round-trip time (RTT) for the low-latency range of power nodes 1-3 is [42,48,45,47,44] ms, the average RTT calculated using the arithmetic mean is approximately 45.2 ms; the RTT for the normal-latency range of power nodes 4-6 is [55,60,58,62,57] ms, and the weighted average RTT calculated using the weighting coefficients [0.2,0.2,0.2,0.2,0.2] is 58.4 ms; the RTT for the high-latency range of power nodes 7-10 is [155,162,158,170,165] ms, and the average RTT calculated using a 10-second sliding window is approximately 162 ms. After integration, the average RTT for power node 1 is 45.2 ms, the average RTT for power node 5 is 58.4 ms, and the average RTT for power node 9 is 162 ms, forming a complete list of average RTTs, providing basic data for subsequent bandwidth optimization and task scheduling.

[0041] The calculation of bandwidth allocation coefficients based on the delay table includes: Create a scheduling list, extract the average round-trip time of each power node in the delay table, and mark the delay status of each power node in the scheduling list according to the delay interval to which the average round-trip time belongs. If the average round-trip time belongs to the low delay interval, mark it as low delay status; if it belongs to the normal delay interval, mark it as normal delay status; and if it belongs to the high delay interval, mark it as high delay status. The system presets bandwidth weights for different latency states and allocation weights for different data stream priorities. For power nodes in low latency states, the bandwidth of the node is preferentially allocated to the high-priority data streams of the node according to the allocation weights. For power nodes in normal latency states, the bandwidth allocation between the high-priority and medium-priority data streams of the node is balanced according to the allocation weights. For power nodes in high latency states, the system guarantees the transmission of the low-priority data streams of the node according to the allocation weights. In one embodiment, the system periodically samples the latency of each power node in the network and records the sampling results in a scheduling list. The scheduling list marks the latency state of each power node, for example, classifying power nodes into low-latency, normal-latency, and high-latency states. At the bandwidth allocation execution entry point, the system combines the power node's latency state with pre-set bandwidth weights, prioritizing the allocation of bandwidth for low-latency power nodes to high-priority data streams. This ensures the real-time transmission of critical data streams (such as control signals or real-time monitoring data) while deferring bandwidth allocation for non-critical data streams. The entire allocation process is automatically completed by the scheduling management module, which generates an initial bandwidth allocation table for reference in subsequent dynamic adjustments.

[0042] In another embodiment, it is assumed that there are 8 power nodes in the network, with sampled average latency of 8ms, 12ms, 10ms, 22ms, 7ms, 15ms, 9ms, and 18ms, respectively. Based on thresholds, the nodes are divided into low-latency power nodes (power nodes 1, 3, 5, and 7), normal-latency power nodes (power nodes 2, 6, and 8), and high-latency power nodes (power node 4). The total bandwidth is 100Mbps, with preset weights of 60% for high-priority data flows, 30% for medium-priority data flows, and 10% for low-priority data flows. When performing bandwidth allocation, high-priority data flows of low-latency nodes receive the maximum bandwidth share, while high-latency nodes are allocated only the remaining bandwidth of low-priority data flows, thereby ensuring the priority and stability of critical service transmissions.

[0043] Set a fixed bandwidth allocation rate, group bandwidth allocation instructions by power node, and push the bandwidth allocation instructions to each power node in batches; The link utilization rate, packet loss rate and buffer queue length of each power node are collected in real time as network occupancy indicators. The bandwidth allocation coefficient of the corresponding power node is dynamically adjusted according to the deviation between the network occupancy indicators and the preset indicator thresholds. In one embodiment, bandwidth allocation is distributed in batches, with each batch covering a preset number of power nodes and sending bandwidth allocation instructions at a preset rate to avoid instantaneous network congestion. Upon receiving the bandwidth instruction, each power node collects its own network occupancy metrics in real time, including link utilization, packet loss rate, and buffer queue length, and feeds these metrics back to the dispatch center. The dispatch center dynamically adjusts the bandwidth allocation coefficient based on these metrics: when a power node's occupancy exceeds the upper limit, its bandwidth allocation share is reduced; when its occupancy falls below the lower limit, its bandwidth allocation share is increased. This closed-loop adjustment achieves balanced bandwidth allocation among multiple nodes and real-time data flow optimization.

[0044] In another embodiment, it is assumed that bandwidth is distributed in batches every 0.3 seconds, with each batch covering two power nodes. The collected real-time network occupancy rates are [65%, 72%, 88%, 42%, 57%, 91%, 63%, 49%]. The dispatch center detects that the occupancy rates of power nodes 3 and 6 exceed 85%, automatically reduces their bandwidth allocation coefficient by 10%, and transfers the released bandwidth to nodes 4 and 8. After the adjustment, the occupancy rates of each power node tend to be balanced, distributed between 55% and 75%, thereby ensuring the stable transmission of critical data flows and the efficient utilization of overall network resources.

[0045] The available bandwidth share for each power node is determined by the bandwidth allocation factor, which includes: The bandwidth occupancy change rate of each power node is calculated using the bandwidth allocation coefficient. The bandwidth usage trend of each power node is determined by the bandwidth occupancy change rate. The positive and negative signs of the bandwidth usage trend of each power node are analyzed to identify the current bandwidth status of the power node and obtain the dynamic trend of node bandwidth. The bandwidth status includes bandwidth strain and bandwidth idle status. A positive sign corresponds to bandwidth strain and a negative sign corresponds to bandwidth idle status. In one embodiment, the system first collects the bandwidth usage of each power node in real time and calculates the bandwidth occupancy change rate of each power node based on a preset bandwidth allocation coefficient. By analyzing the change trend within a continuous sampling period, the system parses the positive or negative sign of the change rate to identify whether the power node is currently in a bandwidth-scarce or idle state. A bandwidth-scarce state indicates that its bandwidth occupancy is continuously increasing, potentially indicating a transmission bottleneck; a bandwidth-idle state indicates that bandwidth occupancy is decreasing, indicating available bandwidth redundancy. The system records the dynamic bandwidth trend of each power node in a node status table, providing a reference for subsequent link capacity allocation and scheduling strategies.

[0046] In another embodiment, assuming there are 6 power nodes in the network, the bandwidth usage (in Mbps) of the nodes measured over 5 consecutive sampling periods is as follows: Power node 1: 50, 55, 60, 63, 65; Power node 2: 30, 28, 27, 25, 24; Power node 3: 70, 72, 74, 77, 80; Power node 4: 40, 42, 41, 39, 37; Power node 5: 55, 58, 60, 63, 66; Power node 6: 20, 22, 24, 25, 27. Based on the sign of the rate of change, the bandwidth usage of power nodes 1, 3, 5, and 6 shows an upward trend, indicating a bandwidth shortage; while power nodes 2 and 4 show a downward trend, indicating a bandwidth idle state. This dynamic trend in bandwidth usage is used for subsequent bandwidth priority allocation and scheduling decisions.

[0047] Cross-validation of link capacity allocation strategies is performed based on the dynamic trend of power node bandwidth. If the validation result is consistent with the dynamic trend of power node bandwidth, the network scheduling code is recorded. A bandwidth allocation vector is constructed based on the network scheduling code. The available bandwidth prediction value of each power node is derived based on the bandwidth allocation vector. The available bandwidth share of each power node is determined based on the available bandwidth prediction value.

[0048] In one embodiment, the system cross-validates the dynamic bandwidth trend of each power node with the current link capacity allocation strategy to determine whether the strategy is consistent with the bandwidth change trend of the power nodes. If consistent, a network scheduling code is generated to identify the current scheduling state. The system constructs a bandwidth allocation vector based on the network scheduling code, and the bandwidth allocation vector is used to deduce the predicted available bandwidth value for each power node. Finally, based on the predicted available bandwidth value, the available bandwidth share of each node is determined, and bandwidth is preferentially allocated to nodes corresponding to high-priority data flows, thereby achieving dynamic balancing and real-time optimization of network resources.

[0049] In another embodiment, assuming that cross-validation yields network scheduling codes of 1, 0, 1, 0, 1, and 1 for the six power nodes, where 1 indicates that the policy result is consistent with the dynamic trend of power node bandwidth, and 0 indicates that the policy result is inconsistent with the dynamic trend of power node bandwidth. After constructing a bandwidth allocation vector based on the scheduling codes, the system extrapolates the predicted available bandwidth (in Mbps) for each power node as follows: power node 1 is 70, power node 2 is 35, power node 3 is 85, power node 4 is 40, power node 5 is 75, and power node 6 is 30. When determining the available bandwidth share for each power node based on the predicted values, high-priority data streams are allocated to power nodes 1, 3, and 5, and low-priority data streams are allocated to power nodes 2, 4, and 6, achieving dynamic bandwidth allocation and ensuring the stability and real-time performance of data stream transmission.

[0050] The construction of the bandwidth allocation vector based on the network scheduling code includes: Obtain the allocation instruction for each power node's smallest unit in the network scheduling code, and map the allocation instruction to the target bandwidth value of the power node's smallest unit; For each power node's smallest unit, the target bandwidth value is weighted and fused with the power node's historical bandwidth occupancy value to generate a preliminary bandwidth allocation vector; In one embodiment, the system parses the network scheduling code of each power node, extracts the allocation instruction of the smallest unit contained therein, and maps the allocation instruction to the target bandwidth value of the smallest unit of each power node. The target bandwidth value is then weighted and fused with the historical bandwidth occupancy value of the power node to generate a preliminary bandwidth allocation vector. The weighting and fusion can be dynamically adjusted according to node priority and historical occupancy; for example, high-priority nodes have a weight of 0.7, and low-priority nodes have a weight of 0.3, thereby balancing historical trends with current allocation needs. The generated preliminary bandwidth allocation vector will serve as input for subsequent conflict detection and correction, providing basic data for link capacity allocation.

[0051] In another embodiment, assume there are 4 power nodes in the network, each allocated 4 minimum units (in Mbps). The historical bandwidth occupancy values ​​(average of 3 consecutive sampling periods) of the nodes are as follows: Power node 1 is [12, 15, 14]; Power node 2 is [8, 9, 7]; Power node 3 is [20, 22, 21]; Power node 4 is [5, 6, 5]. After parsing the network scheduling code, the target bandwidth values ​​of the minimum units of each power node are [10, 12, 15, 13] for power node 1, [6, 7, 8, 7] for power node 2, [18, 20, 22, 21] for power node 3, and [4, 5, 5, 6] for power node 4. After weighted fusion (node ​​weight 0.6 for history, 0.4 for scheduling code), the preliminary bandwidth allocation vector is obtained: Power Node 1 [12.8, 14.2, 14.6, 13.8], Power Node 2 [6.8, 7.4, 7.6, 7.2], Power Node 3 [19.2, 21.2, 21.6, 21], Power Node 4 [4.6, 5.4, 5, 5.2]. This preliminary bandwidth allocation vector serves as the basis for the next step of allocation conflict detection.

[0052] Among them, the allocation conflict anomaly identified based on the initial bandwidth allocation vector includes: A physical link table for power nodes is established based on the initial bandwidth allocation vector. The physical link table is used to identify shared nodes. The vector intervals of the shared nodes are cross-compared one by one to determine the overlapping time period of bandwidth allocation. In one embodiment, the system first establishes a physical link table for each power node in the network based on the preliminary bandwidth allocation vector, recording the upstream and downstream link information connected to each power node and the minimum unit bandwidth value. Subsequently, the system traverses the physical link table, identifies shared nodes (i.e., power nodes that exist on multiple links simultaneously), and cross-references the bandwidth allocation vector intervals of shared nodes one by one. By comparing the bandwidth occupancy time periods and value changes of shared nodes in each link, it can determine whether there are overlapping time periods in bandwidth allocation, providing basic information for conflict detection.

[0053] In another embodiment, assume there are three links in the network, connecting nodes ABC, BD, and CDE respectively. The initial bandwidth allocation vector (in Mbps) is as follows: Node A [10,12,11], Node B [15,18,16], Node C [12,14,13], Node D [20,22], Node E [8,9]. After establishing the node physical link table, shared nodes B and D are identified. A cross-comparison is performed on the vector interval of node B across links ABC and BD. Both links are allocated 18 Mbps in the second time period, indicating an overlapping time period. The same process is applied to node D, with a bandwidth allocation of 20 Mbps for the first time period. This information will be used for subsequent conflict marking and anomaly identification.

[0054] During the overlapping period of bandwidth allocation, conflicting nodes are marked, and conflicting node information is read based on the conflicting nodes. The total bandwidth between power nodes is compared to determine the allocation conflict anomaly. In one embodiment, the system marks the corresponding power nodes as conflict nodes based on the identified bandwidth overlap time periods. Detailed information about the conflict nodes is read, including the link they belong to, the bandwidth usage values ​​for each time period, and the node priority. The total bandwidth of the conflict nodes is compared, and it is calculated whether the total bandwidth usage exceeds the link's maximum capacity threshold. If it does, the system is determined to have an abnormal allocation conflict. The system further takes corrective measures, such as proportionally adjusting or reallocating the bandwidth of the conflict nodes, to ensure the rational utilization of network resources and link security.

[0055] In another embodiment, assume that conflicting nodes B and D are marked over three consecutive time periods. The total bandwidth of node B in each time period is [28, 36, 30] Mbps, and the total bandwidth of node D is [20, 22] Mbps. The maximum link capacity threshold is 30 Mbps. Node B exceeds the threshold in the second time period (36 Mbps), indicating an allocation conflict anomaly; node D does not exceed the threshold in any time period, therefore it is not considered an anomaly. This determination can serve as the basis for the network scheduling algorithm to adjust the bandwidth allocation vector to avoid link congestion and bandwidth waste.

[0056] The total bandwidth of the smallest connected power nodes is summed and compared with the maximum carrying bandwidth threshold to identify the smallest power node that exceeds the link capacity limit. Conflict correction is performed based on the smallest unit of power nodes that exceed the link capacity limit, and a bandwidth allocation vector is constructed.

[0057] In one embodiment, the system performs conflict detection on each power node and its smallest unit based on the initial bandwidth allocation vector, calculates the total bandwidth of connected power node smallest units, and compares it with the maximum link capacity threshold. When the total bandwidth exceeds the link capacity limit, the power node smallest unit exceeding the capacity is identified. Conflict correction is performed on the power node smallest units, for example, by proportionally reducing or adjusting their priorities, ultimately generating a bandwidth allocation vector that conforms to the link capacity constraints to ensure the security and rationality of network resource allocation.

[0058] In another embodiment, assume that the sum of the minimum unit values ​​(in Mbps) of the power nodes connected to power nodes 1-4 are 55, 28, 85, and 18 respectively, and the maximum bandwidth threshold for each link is 50 Mbps. The system identifies that the sum of the minimum unit values ​​of power nodes 1 and 3 exceeds the threshold, requiring conflict correction. By proportionally reducing the excess bandwidth (5% reduction for node 1 and 6% reduction for node 3), the adjusted final bandwidth allocation vector is: power node 1 [12.2, 13.5, 13.8, 13.1], power node 2 [6.8, 7.4, 7.6, 7.2], power node 3 [18, 19.9, 20.3, 19.7], power node 4 [4.6, 5.4, 5, 5.2]. This bandwidth allocation vector satisfies the link capacity constraint while preserving the bandwidth requirements of each power node as much as possible, achieving reasonable resource scheduling.

[0059] Step S2: Allocate available bandwidth to power nodes, detect the network status of each power node, and dynamically adjust the bandwidth ratio in the uplink and downlink directions according to the network status; The dynamic adjustment of the uplink and downlink bandwidth ratio based on network status includes: calculating the ratio of the uplink bandwidth occupancy per unit time to the total uplink bandwidth as the instantaneous occupancy rate, and determining the uplink bandwidth competition intensity of each power node by the magnitude of the instantaneous occupancy rate. Each power node is assigned a ranking number based on the intensity of uplink bandwidth competition, from highest to lowest. Uplink bandwidth shares are then allocated according to the order of the ranking numbers, with power nodes ranked earlier receiving a larger share of uplink bandwidth. The number of instructions transmitted per unit time by downlink nodes is used as the instruction transmission density. Nodes whose instruction transmission density exceeds a preset density threshold are marked as downlink congestion points. The time difference between sending and receiving instructions at congestion points is continuously monitored as the instruction latency. The increase in bandwidth is calculated based on the difference between the instruction latency and the preset latency threshold, and the downlink bandwidth share is allocated to each downlink node according to the increase in bandwidth. If the uplink bandwidth allocation value exceeds the maximum carrying capacity of the corresponding power node link, the uplink bandwidth allocation value of the power node is limited to a fixed percentage of the maximum carrying capacity, the power node is marked as a bandwidth-limited node, and the remaining unallocated uplink bandwidth is reallocated to the power node with the next highest sequence number. In one embodiment, during the allocation process, if the allocated uplink bandwidth share exceeds the maximum carrying capacity of the corresponding power node link, the allocated bandwidth for that power node is limited to 80%-90% of the maximum carrying capacity, with 10%-20% redundancy reserved to prevent sudden loads. The power node is then marked as having limited bandwidth, and the remaining unallocated uplink bandwidth is redistributed to the next sorted node. The above operation is repeated until all available uplink bandwidth is fully allocated.

[0060] In another embodiment, assume there are five power nodes N1–N5 in the network, with maximum link capacities of 30Mbps, 25Mbps, 20Mbps, 35Mbps, and 28Mbps, respectively. After initial bandwidth allocation, N1 is allocated 32Mbps, N2 22Mbps, N3 18Mbps, N4 40Mbps, and N5 25Mbps. The system detects that the allocated values ​​for N1 and N4 exceed their respective capacities, so it limits the bandwidth of N1 to 27Mbps (90%) and the bandwidth of N4 to 31.5Mbps (90%), and marks them as limited bandwidth. The remaining available bandwidth is redistributed to N2, N3, and N5, with the final allocation values ​​as follows: N1 27Mbps, N2 24Mbps, N3 19Mbps, N4 31.5Mbps, and N5 28Mbps. This bandwidth allocation method provides necessary redundancy for sudden network loads while ensuring that nodes are not overloaded, and at the same time achieves full utilization of overall bandwidth resources.

[0061] The formula for calculating the allocation of uplink bandwidth share based on the order of the sequence number is as follows:

[0062] in, Let be the uplink bandwidth share of the i-th power node. Let N be the instantaneous uplink occupancy rate of the i-th power node, and N be the total number of power nodes participating in uplink bandwidth allocation. This represents the total available uplink bandwidth. In one embodiment, the instantaneous uplink occupancy rate of each power node is collected, and the uplink bandwidth contention intensity of the nodes is calculated based on the occupancy rate. Subsequently, a ranking number is assigned to each power node according to the contention intensity, and an uplink bandwidth share is allocated to each power node according to the ranking number. Assume there are 5 power nodes N1–N5 in the network, with instantaneous uplink occupancy rates of [0.6, 0.3, 0.5, 0.8, 0.4], and a total available uplink bandwidth of 100Mbps. The node ranking numbers calculated according to the instantaneous uplink occupancy rate are N4>N1>N3>N5>N2, corresponding to uplink bandwidth shares of 28Mbps, 22Mbps, 20Mbps, 18Mbps, and 12Mbps, respectively.

[0063] The formula for allocating downlink bandwidth shares to each downlink node according to the increase in bandwidth is as follows:

[0064] in, Let i be the downlink bandwidth share of the i-th power node. For the basic bandwidth of power nodes, For instruction latency, This is the bandwidth adjustment factor; In one embodiment, the command transmission density of the downlink nodes of each power node is collected, and downlink congestion points are identified. Command latency of congested nodes is continuously monitored, and the bandwidth increase ratio is calculated based on the latency to allocate downlink bandwidth shares. Assume the command transmission density of downlink nodes N1–N5 is [50, 30, 40, 60, 35] messages / second, and downlink congestion points are detected at N1 and N4. The command latency at five consecutive time points is as follows: N1: [95, 100, 105, 110, 102] ms, N4: [120, 135, 110, 140, 125] ms, and the latency of the remaining nodes is as follows: N2: [60, 65, 70, 68, 63], N3: [58, 62, 64, 61, 59], N5: [55, 57, 60, 62, 56] ms. =10Mbps, =0.1, and the calculated downlink bandwidth shares of downlink nodes N1–N5 are 15Mbps, 10Mbps, 12Mbps, 28Mbps, and 10Mbps, respectively.

[0065] The uplink bandwidth allocation and downlink bandwidth share are integrated into a single comprehensive bandwidth share, which is expressed mathematically as follows:

[0066] That , These are the weighting coefficients.

[0067] In one embodiment, the allocated uplink bandwidth share and the allocated downlink bandwidth share are integrated to obtain the overall bandwidth share for each node. The overall bandwidth share can be obtained by mathematical addition or weighted summation. For example, combining the uplink bandwidth share and the downlink bandwidth share, the overall bandwidth (Mbps) share is as follows: Node N1's uplink bandwidth share is 22, Node N1's downlink bandwidth share is 15, resulting in an overall bandwidth share of 37; Node N2's uplink bandwidth share is 12, Node N2's downlink bandwidth share is 10, resulting in an overall bandwidth share of 22; Node N3's uplink bandwidth share is 20, Node N3's downlink bandwidth share is 12, resulting in an overall bandwidth share of 32; Node N4's uplink bandwidth share is 28, Node N4's downlink bandwidth share is 28, resulting in an overall bandwidth share of 56; Node N5's uplink bandwidth share is 18, Node N5's downlink bandwidth share is 10, resulting in an overall bandwidth share of 28. This overall bandwidth share can be used for node priority ranking, link load balancing, and future bandwidth prediction.

[0068] Step S3: Prioritize data streams according to bandwidth ratio, perform multi-point remote collaborative simulation based on data stream priority, and record the transmission anomaly queue if the packet loss rate of the power node is higher than the preset packet loss threshold. Multi-point remote collaborative simulation based on data stream priority includes: dividing the data to be transmitted by each power node into multiple priority queues according to the data stream priority from high to low. Each priority queue contains only the same priority data stream of a single power node, and all priority queues form a candidate scheduling queue set. Multi-point remote collaborative simulation is started according to the preset simulation duration. Data streams in the candidate scheduling queue are transmitted in order of priority. The total number of data packets sent and received, link occupancy rate and round-trip delay of each power node are recorded in real time. The packet loss rate of each power node is calculated based on the total number of data packets sent and the total number of data packets successfully received. Power nodes with packet loss rates higher than the preset packet loss threshold and their corresponding priority queue information are included in the transmission anomaly queue.

[0069] In this embodiment, the data streams to be transmitted by each power node are divided into priority queues based on the bandwidth ratio of each power node. Each priority queue corresponds to a set of data streams of a power node, and a scheduling algorithm allocates available bandwidth to high-priority queues first. During multi-point remote collaborative simulation, the packet loss rate, link occupancy rate, and round-trip latency of each power node are recorded. If the packet loss rate of a power node exceeds a preset packet loss threshold (e.g., 5%), it is marked as an abnormal node and added to the transmission abnormal queue, providing a basis for subsequent task reallocation.

[0070] In another embodiment, the multi-point remote collaborative simulation results showed that the packet loss rate of power nodes 1-4 was 2%-4%, the packet loss rate of power nodes 5-8 was 6%-8%, and the packet loss rate of power nodes 9-12 was 12%-15%. Therefore, power nodes 5-12 were added to the transmission anomaly queue for bandwidth optimization and task migration.

[0071] If the packet loss rate of a power node exceeds a preset packet loss threshold, the abnormal transmission queue is recorded by: converting the data to be transmitted into a priority queue based on the data stream priority, with each priority queue corresponding to a data stream set of a power node, forming a candidate scheduling queue set; and performing remote collaborative simulation among the power nodes based on the candidate scheduling queue set to generate a simulation report.

[0072] In this embodiment, the data to be transmitted is divided into multiple priority queues according to the priority of each data stream in the network. Each priority queue corresponds to a set of data streams of a power node, thus forming a set of candidate scheduling queues. Based on the set of candidate scheduling queues, the system performs remote collaborative simulation among the power nodes and generates a simulation report to evaluate the data transmission load, latency, and potential congestion of each power node under different priorities, providing a basis for subsequent scheduling strategy optimization.

[0073] In another embodiment, the network is assumed to contain six power nodes N1–N6, with total data streams to be transmitted of 120Mb / s, 80Mb / s, 100Mb / s, 90Mb / s, 110Mb / s, and 95Mb / s respectively, divided into high, medium, and low priority queues. Through remote collaborative simulation, a simulation report is generated. The results show that power nodes N1 and N4 experience localized load peaks in the medium-high priority queues, power nodes N3 and N5 have slightly higher transmission latency in the low priority queues, while power nodes N2 and N6 have relatively stable overall load. The simulation report records the average latency, throughput, and load distribution of each queue, facilitating subsequent packet loss rate calculations and abnormal node identification.

[0074] The simulation report is used to calculate the packet loss rate of the nodes. If the packet loss rate of the power nodes is higher than the preset packet loss threshold, the abnormal packet loss nodes are marked and a list of abnormal packet loss nodes is generated. The transmission anomaly queue of the list of abnormal packet loss nodes is recorded.

[0075] In one embodiment, a simulation report is used to calculate the packet loss rate of each power node in each priority queue. If the packet loss rate of a power node exceeds a preset threshold, it is marked as an abnormal packet loss node, and a list of abnormal packet loss nodes is generated. At the same time, the transmission anomalies of the power node in each queue are recorded to provide a reference for subsequent retransmission, bandwidth adjustment, or scheduling optimization.

[0076] In another embodiment, the packet loss threshold is assumed to be 3%. Simulation results show that the packet loss rate of the high-priority queue of power node N1 is 4.2%, the packet loss rate of the medium-priority queue of power node N4 is 3.5%, and the packet loss rate of the remaining power nodes is all below 2%. Power nodes N1 and N4 are marked as abnormal packet loss nodes, and a list of abnormal packet loss nodes is generated. At the same time, the abnormal queue of power node N1 is recorded as a high-priority queue, and the abnormal queue of power node N4 is recorded as a medium-priority queue, which facilitates the subsequent rescheduling of priority queues or the implementation of redundant transmission strategies.

[0077] Step S4: Perform task reallocation based on the transmission anomaly queue, determine the bandwidth optimization allocation share, and use the bandwidth optimization allocation share to correct the transmission anomaly queue in order to execute multi-point remote collaborative interaction tasks; Task reallocation based on the transmission anomaly queue includes: extracting the identification information of each abnormal power node in the transmission anomaly queue, locating the physical link where the abnormal power node is located, and collecting the ratio of the bandwidth occupancy of each physical link per unit time to the maximum carrying bandwidth of the link as the link occupancy rate. Physical links with a link occupancy rate higher than a first preset threshold are marked as high-load links, and physical links with a link occupancy rate lower than a second preset threshold are marked as low-load links. In one embodiment, the link resources occupied by each abnormal node in the transmission anomaly queue are analyzed. Links with a occupancy rate exceeding 80% are marked as high-load links, and links with a occupancy rate below 50% are marked as low-load links. Low-priority tasks on high-load links are preferentially migrated to low-load links, while link occupancy changes are monitored in real time, and bandwidth allocation is dynamically adjusted for optimization. After task migration is completed, bandwidth allocation continues to be optimized for the corrected abnormal nodes, ensuring the continuity and stability of multi-point remote collaborative interaction tasks.

[0078] In another embodiment, assuming that the link occupancy rates of power nodes 6, 7, and 10 all exceed 80%, their low-priority tasks are migrated to low-load links with occupancy rates of 40%–45%. After the migration is completed, the link occupancy rate drops to 70%–75%, and the transmission anomaly queue is updated to power nodes 5, 8, 9, 11, and 12, ensuring stable transmission of critical data streams in collaborative tasks.

[0079] In one embodiment, the locations of abnormal nodes in the network are determined based on the recorded transmission anomaly queue. Link occupancy is obtained at each abnormal node location, and the occupancy rate is analyzed: links with an occupancy rate higher than 80% are marked as high-load links, and links with an occupancy rate lower than 50% are marked as low-load links. This marking information can be used for subsequent task scheduling, load balancing, and traffic optimization strategy formulation.

[0080] In another embodiment, assume the network contains power nodes N1–N5, and anomalous nodes are located at N2 and N4. After obtaining link occupancy information, the link occupancy rates of anomalous node N2 are 82%, 45%, and 67%, respectively, while those of anomalous node N4 are 90%, 35%, and 50%, respectively. Based on these link occupancy rates, the first link of anomalous node N2 and the first link of anomalous node N4 are marked as high-load links, the second link of anomalous node N2 and the second link of anomalous node N4 are marked as low-load links, and the remaining links are marked as medium-load links. This marking result provides a clear basis for subsequent task migration.

[0081] Identify all data streams carried on high-load links, filter out low-priority data streams as non-critical tasks, and migrate non-critical tasks to low-load links. During the migration process, the link occupancy rate of high-load links and low-load links is collected once per second. The bandwidth allocation is dynamically adjusted based on the changes in link occupancy rate to keep the high-load link occupancy rate within a preset reasonable range and the low-load link occupancy rate does not exceed the preset upper limit.

[0082] In one embodiment, the system utilizes marked high-load links to migrate non-critical tasks from high-load links to low-load links. During the migration process, the system monitors the occupancy rate of each link in real time and dynamically adjusts task allocation to avoid new congestion and ensure network load balancing and data transmission continuity.

[0083] In another embodiment, assuming that during the migration process, the initial occupancy rate of high-load links on power node N2 is 82%, and after migrating some non-critical tasks to low-load links, the occupancy rate drops to 65%, while the low-load link occupancy rate increases from 45% to 60%. On power node N4, the high-load link occupancy rate decreases from 90% to 70%, while the low-load link occupancy rate increases from 35% to 55%. Throughout the migration process, the system updates link occupancy data every second and adjusts task allocation based on real-time occupancy rates, keeping the high-load link occupancy rate below 70% and the low-load link occupancy rate below 65%, thereby effectively preventing link overload and ensuring priority transmission of critical tasks.

[0084] Example 2: like Figure 2 As shown, this embodiment also provides a multi-point remote collaborative interaction system based on power communication network operation and maintenance, including a latency acquisition module 1, a bandwidth allocation module 2, a collaborative simulation module 3, and a task reassignment module 4; The latency acquisition module 1 collects the periodic round-trip latency between each power node and the central node, forms a latency table, calculates the bandwidth allocation coefficient based on the latency table, and determines the available bandwidth share of each power node through the bandwidth allocation coefficient. Bandwidth allocation module 2 allocates available bandwidth to power nodes, detects the network status of each power node, and dynamically adjusts the bandwidth ratio in the uplink and downlink directions according to the network status. The bandwidth allocation module also includes a status marking unit, which is used to create a scheduling list, extract the average round-trip time of each power node in the delay table, and mark the delay status of each power node in the scheduling list according to the delay interval to which the average round-trip time belongs. The weight allocation unit is used to preset the bandwidth weights corresponding to different delay states and the allocation weights corresponding to different data flow priorities, and to allocate the bandwidth of the corresponding data flow to the power nodes with different delay states according to the allocation weights. The coefficient adjustment unit is used to set the bandwidth allocation issuance rate, push bandwidth allocation instructions in batches, collect network occupancy indicators in real time, and dynamically adjust the bandwidth allocation coefficient based on the network occupancy indicators. The share determination unit is used to calculate the bandwidth occupancy change rate using the bandwidth allocation coefficient, determine the dynamic trend of node bandwidth, record the network scheduling code and construct the bandwidth allocation vector, deduce the available bandwidth prediction value based on the bandwidth allocation vector, and determine the available bandwidth share of each power node.

[0085] Collaborative simulation module 3 prioritizes data streams based on bandwidth ratios and performs multi-point remote collaborative simulations based on these priorities. If the packet loss rate of a power node exceeds a preset packet loss threshold, it records the transmission anomaly queue. Task reassignment module 4 performs task reassignment based on the transmission anomaly queue, determines the bandwidth optimization allocation share, and uses the bandwidth optimization allocation share to correct the transmission anomaly queue in order to execute multi-point remote collaborative interaction tasks.

[0086] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. The methods disclosed in the embodiments are described simply because they correspond to the systems disclosed in the embodiments; relevant details can be found in the method section.

[0087] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0088] In the embodiments provided by this invention, it should be understood that the disclosed systems, methods, and approaches can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between systems or units may be electrical, mechanical, or other forms.

[0089] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0090] In addition, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit.

[0091] Similarly, in the various embodiments of the present invention, each processing unit can be integrated into a functional module, or each processing unit can exist physically, or two or more processing units can be integrated into a functional module.

[0092] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0093] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0094] The above-disclosed embodiments are merely preferred embodiments of the present invention, but the present invention is not limited thereto. Any non-creative variations that can be conceived by those skilled in the art, as well as any improvements and modifications made without departing from the principles of the present invention, should fall within the protection scope of the present invention.

Claims

1. A multi-point remote collaborative interaction method based on power communication network operation and maintenance, characterized in that, Includes the following steps: Step S1: Collect the periodic round-trip delay between each power node and the central node to form a delay table. Calculate the bandwidth allocation coefficient based on the delay table and determine the available bandwidth share for each power node using the bandwidth allocation coefficient. Step S2: Allocate available bandwidth to power nodes, detect the network status of each power node, and dynamically adjust the bandwidth ratio in the uplink and downlink directions according to the network status; Step S3: Prioritize data streams according to bandwidth ratio, perform multi-point remote collaborative simulation based on data stream priority, and record the transmission anomaly queue if the packet loss rate of the power node is higher than the preset packet loss threshold. Step S4: Perform task reallocation based on the transmission anomaly queue, determine the bandwidth optimization allocation share, and use the bandwidth optimization allocation share to correct the transmission anomaly queue in order to execute multi-point remote collaborative interaction tasks.

2. The multi-point remote collaborative interaction method based on power communication network operation and maintenance according to claim 1, characterized in that, In step S1, the periodic round-trip delay between each power node and the central node is collected to form a delay table, including: sending a timestamped probe signal to each power node through the central node, the power node receiving the probe signal and returning a response message, the central node receiving the response message and recording the sending time and response time of the probe signal, and calculating the single round-trip delay. Arrange multiple consecutive round-trip delays in chronological order to form a delay sampling sequence, divide the time window into fixed lengths, and calculate the average value of all round-trip delays within each time window; Adjust the sliding step size according to the average difference of the single round-trip delay of two adjacent time windows, move the time window according to the adjusted sliding step size, and mark the sampling points where the difference between the single round-trip delay and the average single round-trip delay of the current time window exceeds the preset range as noise residual points. For all noise residue points, spline interpolation is used to correct the data. The corrected time delay sampling sequence is re-divided into time windows and the average value is calculated. The time window shifting and noise correction steps are repeated to generate a smooth time delay characteristic curve. The delay values ​​of each power node are extracted based on the delay characteristic curve. The delay intervals are divided according to the range of delay values. The average round-trip delay of each power node is obtained by using the corresponding average value calculation method for different delay intervals. The identification information and average round-trip delay of all power nodes are summarized to form a delay table.

3. A multi-point remote collaborative interaction method for operation and maintenance based on power communication networks according to claim 2, characterized in that, The delay range is divided into low delay range, normal delay range, and high delay range according to the range of delay values; Among them, The range is divided into a low latency range, and the range of latency values ​​between a preset low latency threshold and a preset high latency threshold is divided into a normal latency range. The range is divided into high-latency intervals; For the low-latency range, the arithmetic mean is used to calculate the average round-trip time, and the mathematical expression is: ,in, For the average round-trip time in the low-latency zone, Let k be the single round-trip delay within the low-latency interval. This represents the total number of round-trip delays within the low-latency interval. For the normal delay range, the average round-trip time is calculated using a weighted average, and the mathematical expression is: ,in, The average round-trip time within the normal delay range. This represents the k-th round-trip delay within the normal delay interval. This is the time weighting coefficient for the k-th single round-trip delay. This represents the total number of round-trip delays within the normal delay interval. For the high-latency interval, the average round-trip time is calculated using a sliding window averaging method. The single round-trip time within the high-latency interval is iterated through using a fixed window length and step size. The average value of each sliding window is calculated and taken as the average round-trip time for the high-latency interval. The average round-trip time of the low-delay interval, the average round-trip time of the normal-delay interval, and the average round-trip time of the high-delay interval are used as the average round-trip time of the corresponding power nodes.

4. A multi-point remote collaborative interaction method for operation and maintenance based on power communication network as described in claim 2, characterized in that, The calculation of bandwidth allocation coefficients based on the delay table includes: Create a scheduling list, extract the average round-trip time of each power node in the delay table, and mark the delay status of each power node in the scheduling list according to the delay interval to which the average round-trip time belongs. If the average round-trip time belongs to the low delay interval, mark it as low delay status; if it belongs to the normal delay interval, mark it as normal delay status; and if it belongs to the high delay interval, mark it as high delay status. The system presets bandwidth weights for different latency states and allocation weights for different data stream priorities. For power nodes in low latency states, the bandwidth of the node is preferentially allocated to the high-priority data streams of the node according to the allocation weights. For power nodes in normal latency states, the bandwidth allocation between the high-priority and medium-priority data streams of the node is balanced according to the allocation weights. For power nodes in high latency states, the system guarantees the transmission of the low-priority data streams of the node according to the allocation weights. Set a fixed bandwidth allocation rate, group bandwidth allocation instructions by power node, and push the bandwidth allocation instructions to each power node in batches; The link utilization rate, packet loss rate, and buffer queue length of each power node are collected in real time as network occupancy indicators. The bandwidth allocation coefficient of the corresponding power node is dynamically adjusted according to the degree of deviation between the network occupancy indicators and the preset indicator thresholds.

5. A multi-point remote collaborative interaction method for operation and maintenance of power communication networks according to claim 4, characterized in that, The available bandwidth share for each power node is determined by the bandwidth allocation factor, which includes: The bandwidth occupancy change rate of each power node is calculated using the bandwidth allocation coefficient. The bandwidth usage trend of each power node is determined by the bandwidth occupancy change rate. The positive and negative signs of the bandwidth usage trend of each power node are analyzed to identify the current bandwidth status of the power node and obtain the dynamic trend of node bandwidth. The bandwidth status includes bandwidth strain and bandwidth idle status. A positive sign corresponds to bandwidth strain and a negative sign corresponds to bandwidth idle status. Cross-validation of link capacity allocation strategies is performed based on the dynamic trend of power node bandwidth. If the validation result is consistent with the dynamic trend of power node bandwidth, the network scheduling code is recorded. Obtain the allocation instruction for each power node's smallest unit in the network scheduling code, and map the allocation instruction to the target bandwidth value of the power node's smallest unit; For each power node's smallest unit, the target bandwidth value is weighted and fused with the power node's historical bandwidth occupancy value to generate a preliminary bandwidth allocation vector; A physical link table for power nodes is established based on the initial bandwidth allocation vector. The physical link table is used to identify shared nodes. The vector intervals of the shared nodes are cross-compared one by one to determine the overlapping time period of bandwidth allocation. During the overlapping period of bandwidth allocation, conflicting nodes are marked, and conflicting node information is read based on the conflicting nodes. The total bandwidth between power nodes is compared to determine the allocation conflict anomaly. The total bandwidth of the smallest connected power nodes is summed and compared with the maximum carrying bandwidth threshold to identify the smallest power node that exceeds the link capacity limit. Conflict correction is performed based on the smallest unit of power nodes that exceed the link capacity limit, and a bandwidth allocation vector is constructed. The available bandwidth of each power node is predicted by extrapolating the bandwidth allocation vector, and the available bandwidth share of each power node is determined based on the predicted available bandwidth.

6. A multi-point remote collaborative interaction method for operation and maintenance based on power communication network according to claim 1, characterized in that, In step S2, dynamically adjusting the bandwidth ratio of uplink and downlink according to the network status includes: calculating the ratio of the bandwidth occupancy of the uplink per unit time to the total bandwidth of the uplink as the instantaneous occupancy rate, and determining the uplink bandwidth competition intensity of each power node by the magnitude of the instantaneous occupancy rate. Each power node is assigned a ranking number based on the intensity of uplink bandwidth competition, from highest to lowest. Uplink bandwidth shares are then allocated according to the order of the ranking numbers, with power nodes ranked earlier receiving a larger share of uplink bandwidth. The number of instructions transmitted per unit time by downlink nodes is used as the instruction transmission density. Nodes whose instruction transmission density exceeds a preset density threshold are marked as downlink congestion points. The time difference between sending and receiving instructions at congestion points is continuously monitored as the instruction latency. The increase in bandwidth is calculated based on the difference between the instruction latency and the preset latency threshold, and the downlink bandwidth share is allocated to each downlink node according to the increase in bandwidth. If the uplink bandwidth allocation value exceeds the maximum carrying capacity of the corresponding power node link, the uplink bandwidth allocation value of the power node is limited to a fixed percentage of the maximum carrying capacity, the power node is marked as a bandwidth-limited node, and the remaining unallocated uplink bandwidth is reallocated to the power node with the next highest sequence number. The formula for calculating the allocation of uplink bandwidth share based on the order of the sequence number is as follows: in, Let be the uplink bandwidth share of the i-th power node. Let N be the instantaneous uplink occupancy rate of the i-th power node, and N be the total number of power nodes participating in uplink bandwidth allocation. This represents the total available uplink bandwidth. The formula for allocating downlink bandwidth shares to each downlink node according to the increase in bandwidth is as follows: in, Let i be the downlink bandwidth share of the i-th power node. For the basic bandwidth of power nodes, For instruction latency, This is the bandwidth adjustment factor; The uplink bandwidth allocation and downlink bandwidth share are integrated into a single comprehensive bandwidth share, which is expressed mathematically as follows: in, , These are the weighting coefficients.

7. A multi-point remote collaborative interaction method for operation and maintenance based on power communication network according to claim 1, characterized in that, In step S3, performing multi-point remote collaborative simulation based on data flow priority includes: dividing the data to be transmitted by each power node into multiple priority queues according to the data flow priority from high to low. Each priority queue contains only the same priority data flow of a single power node, and all priority queues form a candidate scheduling queue set. Multi-point remote collaborative simulation is started according to the preset simulation duration. Data streams in the candidate scheduling queue are transmitted in order of priority. The total number of data packets sent and received, link occupancy rate and round-trip delay of each power node are recorded in real time. The packet loss rate of each power node is calculated based on the total number of data packets sent and the total number of data packets successfully received. Power nodes with packet loss rates higher than the preset packet loss threshold and their corresponding priority queue information are included in the transmission anomaly queue.

8. A multi-point remote collaborative interaction method for operation and maintenance based on power communication network according to claim 1, characterized in that, In step S4, the task reallocation based on the transmission anomaly queue includes: extracting the identification information of each abnormal power node in the transmission anomaly queue, locating the physical link where the abnormal power node is located, and collecting the ratio of the bandwidth occupancy of each physical link per unit time to the maximum carrying bandwidth of the link as the link occupancy rate. Physical links with a link occupancy rate higher than a first preset threshold are marked as high-load links, and physical links with a link occupancy rate lower than a second preset threshold are marked as low-load links. Identify all data streams carried on high-load links, filter out low-priority data streams as non-critical tasks, and migrate non-critical tasks to low-load links. During the migration process, the link occupancy rate of high-load links and low-load links is collected once per second. The bandwidth allocation is dynamically adjusted based on the changes in link occupancy rate to keep the high-load link occupancy rate within a preset reasonable range and the low-load link occupancy rate does not exceed the preset upper limit.

9. A multi-point remote collaborative interactive system based on power communication network operation and maintenance, characterized in that, It includes a latency acquisition module, a bandwidth allocation module, a collaborative simulation module, and a task reallocation module; The latency acquisition module collects the periodic round-trip latency between each power node and the central node, forms a latency table, calculates the bandwidth allocation coefficient based on the latency table, and determines the available bandwidth share of each power node through the bandwidth allocation coefficient. The bandwidth allocation module allocates available bandwidth to power nodes, detects the network status of each power node, and dynamically adjusts the bandwidth ratio in the uplink and downlink directions based on the network status. The collaborative simulation module prioritizes data streams based on bandwidth ratios and performs multi-point remote collaborative simulations based on data stream priorities. If the packet loss rate of a power node exceeds a preset packet loss threshold, a transmission anomaly queue is recorded. The task reassignment module performs task reassignment based on the transmission anomaly queue, determines the bandwidth optimization allocation share, and uses the bandwidth optimization allocation share to correct the transmission anomaly queue in order to execute multi-point remote collaborative interaction tasks.

10. A multi-point remote collaborative interactive system for operation and maintenance based on power communication networks according to claim 9, characterized in that, The bandwidth allocation module also includes: The status marking unit is used to create a scheduling list, extract the average round-trip time of each power node in the delay table, and mark the delay status of each power node in the scheduling list according to the delay interval to which the average round-trip time belongs. The weight allocation unit is used to preset the bandwidth weights corresponding to different delay states and the allocation weights corresponding to different data flow priorities, and to allocate the bandwidth of the corresponding data flow to the power nodes with different delay states according to the allocation weights. The coefficient adjustment unit is used to set the bandwidth allocation issuance rate, push bandwidth allocation instructions in batches, collect network occupancy indicators in real time, and dynamically adjust the bandwidth allocation coefficient based on the network occupancy indicators. The share determination unit is used to calculate the bandwidth occupancy change rate using the bandwidth allocation coefficient, determine the dynamic trend of node bandwidth, record the network scheduling code and construct the bandwidth allocation vector, deduce the available bandwidth prediction value based on the bandwidth allocation vector, and determine the available bandwidth share of each power node.

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